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Model compression and knowledge distillation have been successfully applied for cross-architecture and cross-domain transfer learning.
Multitask learning
Rich Caruana · 1997
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Model compression
C. Buciluǎ, R. Caruana, and A. Niculescu-Mizil · 2006
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Frustratingly easy domain adaptation
Hal Daumé III · 2007
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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A new learning paradigm: Learning using privileged information
Vladimir Vapnik and Akshay Vashist · 2009
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Adapting visual category models to new domains
Kate Saenko, Brian Kulis, Mario Fritz, and Trevor Darrell · 2010
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Describing People: Poselet-Based Approach to Attribute Classification
L. Bourdev, S. Maji, and J. Malik · 2011
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What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
Brian Kulis, Kate Saenko, and Trevor Darrell · 2011
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Learning to align from scratch
Gary Huang, Marwan Mattar, Honglak Lee, and Erik G Learned-Miller · 2012
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Structured forests for fast edge detection
Piotr Dollár and C. Lawrence Zitnick · 2013
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Decaf: A deep convolutional activation feature for generic visual recognition
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, Ning Zhang, E. Tzeng, and T. Darrell · 2013
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Unsupervised visual domain adaptation using subspace alignment
Basura Fernando, Amaury Habrard, Marc Sebban, and Tinne Tuytelaars · 2013
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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Do deep nets really need to be deep?
Jimmy Ba and Rich Caruana · 2014
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Bird species categorization using pose normalized deep convolutional nets
Steve Branson, Grant Van Horn, Serge Belongie, and Pietro Perona · 2014
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Return of the devil in the details: Delving deep into convolutional nets
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
Cited alongside, same era.
Describing textures in the wild
M. Cimpoi, S. Maji, I. Kokkinos, S. Mohamed, , and A. Vedaldi · 2014
Cited alongside, same era.
Rich feature hierarchies for accurate object detection and semantic segmentation
R. B. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Cited alongside, same era.
Distilling knowledge in a neural network
G. Hinton, O. Vinyals, and J Dean · 2014
Cited alongside, same era.
Cnn features off-the-shelf: An astounding baseline for recognition
A. Sharif Razavin, H. Azizpour, J. Sullivan, and S. Carlsson · 2014
Sketch-based 3d shape retrieval using convolutional neural networks
Fang Wang, Le Kang, and Yi Li · 2015
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Soundnet: Learning sound representations from unlabeled video
Yusuf Aytar, Carl Vondrick, and Antonio Torralba · 2016
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Domain separation networks
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, and Dumitru Erhan · 2016
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Cross modal distillation for supervision transfer
Saurabh Gupta, Judy Hoffman, and Jitendra Malik · 2016
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Cross-modal adaptation for rgb-d detection
Judy Hoffman, Saurabh Gupta, Jian Leong, Sergio Guadarrama, and Trevor Darrell · 2016
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Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Deep domain confusion: Maximizing for domain invariance
Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell · 2014
Cited alongside, same era.
Deep filter banks for texture recognition and description
M. Cimpoi, S. Maji, and A. Vedaldi · 2015
Cited alongside, same era.
Spatial transformer networks
Max Jaderberg, Karen Simonyan, and Andrew Zisserman · 2015
Cited alongside, same era.
Fine-grained recognition without part annotations
Jonathan Krause, Hailin Jin, Jianchao Yang, and Li Fei-Fei · 2015
Cited alongside, same era.
Bilinear cnn models for fine-grained visual recognition
Tsung-Yu Lin, Aruni RoyChowdhury, and Subhransu Maji · 2015
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Learning representations for automatic colorization
Gustav Larsson, Michael Maire, and Gregory Shakhnarovich · 2016
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2016
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Coupled generative adversarial networks
Ming-Yu Liu and Oncel Tuzel · 2016
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Unifying distillation and privileged information
D. Lopez-Paz, L. Bottou, B. Schölkopf, and V. Vapnik · 2016
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Ambient sound provides supervision for visual learning
Andrew Owens, Jiajun Wu, Josh H McDermott, William T Freeman, and Antonio Torralba · 2016
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Fine-to-coarse knowledge transfer for low-res image classification
Xingchao Peng, Judy Hoffman, Stella X. Yu, and Kate Saenko · 2016
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Return of frustratingly easy domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2016
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Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Unsupervised pixel-level domain adaptation with generative adversarial networks
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, and Dilip Krishnan · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Trevor Darrell, and Kate Saenko · 2017
Closest in time.